grok-code-fast-1: benchmark scores, price and ranking
grok-code-fast-1 from xAI ranks #641 of 743 LLMs on the LLMs Tiger aggregate benchmark score (44.3), based on 4 benchmark results captured up to 2026-10-13.
- Organisation
- xAI
- Type
- Frontier model
- Open weights
- No
- Cheapest API price
- $0.200 in / $1.50 out per million tokens (via azure_ai, observed 2026-10-13T20:47Z)
- Aggregate rank
- #641 of 743 (score 44.3)
Relative to other models, grok-code-fast-1 is strongest on ALE-Bench (#56 of 79) and weakest on WebDev Arena (#66 of 67).
Across the 4 benchmarks where at least ten models are scored, grok-code-fast-1 is in the top 10% on 0 and in the top half on 0.
Its cheapest listed input price, $0.200 per million tokens, is lower than that of 67% of the 427 models with a listed price.
grok-code-fast-1 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| ALE-Bench | 588 | #56 of 79 | Epoch AI Benchmarking Hub | 2026-10-13 |
| WeirdML | 35.1% | #81 of 109 | Epoch AI Benchmarking Hub | 2026-10-13 |
| Terminal-Bench 2.0 | 25.8% | #23 of 28 | Epoch AI Benchmarking Hub | 2026-10-13 |
| WebDev Arena | 1,165 | #66 of 67 | Epoch AI Benchmarking Hub | 2026-10-13 |
About grok-code-fast-1
grok-code-fast-1 is a frontier model from xAI. The cheapest API listing we track charges $0.200 per million input tokens and $1.50 per million output tokens, through azure_ai. We hold 4 benchmark results for it across 2 areas, and none is in the top tenth of its board.
Where grok-code-fast-1 stands
On our aggregate score, grok-code-fast-1 is #641 of 743 ranked models, in the lower half. Its score is 44.3; the scale is centred on 50, so it sits 5.7 points below the typical model. That beats 14% of the ranked field. Among the 26 ranked xAI models it is #25. The next one up is grok-build-0.1 at 45.4. The next one down is grok-2-1212 at 43.4.
grok-code-fast-1, benchmark by benchmark
grok-code-fast-1 lands below the middle on ALE-Bench: 588, #56 of 79, with 70% of the field scoring higher. GPT-6 Astra (max) leads at 2,951; the closest result above is Kimi K2 Thinking at 598. It covers AtCoder heuristic-optimisation contests (performance rating). The board median is 764, so grok-code-fast-1 is 176 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
grok-code-fast-1 lands below the middle on WeirdML: 35.1%, #81 of 109, with 73% of the field scoring higher. GPT-6 Astra (max) leads at 93.3%; the closest result above is Gemma 4 26B A4B at 35.2%. It covers unusual machine-learning tasks. The board median is 41.2%, so grok-code-fast-1 is 6.1 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Terminal-Bench 2.0 is a weak spot. grok-code-fast-1 scores 25.8%, #23 of 28, behind 79% of the models measured. The leader, Gemini 3 Pro Preview, reaches 69.4%. It covers real terminal tasks (agent + model). The board median is 37.3%, so grok-code-fast-1 is 11.5 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
WebDev Arena is a weak spot. grok-code-fast-1 scores 1,165, #66 of 67, behind 97% of the models measured. The leader, Claude Opus 5.5 (max), reaches 1,820. It covers building web apps, crowd-voted (Elo). The board median is 1,433, so grok-code-fast-1 is 268 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Strengths and weaknesses
Software engineering: weak, ahead of 16% of the field on average across 3 benchmarks. Its best board here is ALE-Bench (#56 of 79) and its weakest is WebDev Arena (#66 of 67).
Price and value
The median input price across the 427 priced models is $0.500 per million tokens, so grok-code-fast-1 costs less than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on MiniMax-M3 ($0.230) and MiniMax-M2.7 ($0.250).
Reading these numbers
The 4 scores on this page come from 1 source: Epoch AI Benchmarking Hub (4). No official leaderboard supplied any of them, so treat them as third-party measurements. With 4 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #638 Yi-1.5-34B-Chat (44.4)
- #639 granite-4.1-3b (44.4)
- #640 Laguna M.1 (44.4)
- #642 Qwen1.5-7B-Chat (44.3)
- #643 GPT-4o (May 2024) (44.3)
- #644 gpt-oss-20b (high) (44.3)
More from xAI
- Grok 4.6 (xhigh) (#34, 53.6)
- grok-4-0709 (#38, 53.2)
- Grok 4 (#39, 53.2)
- Grok 4.7 (xhigh) (#41, 53.1)
- Grok 4.5 (high) (#85, 52.0)
- Grok 4.20 (Reasoning) (#136, 51.2)
Compare it on the live leaderboard → · How the aggregate score works